What problem does it solve? Teams routinely pick research methods by habit or budget — running surveys for behavioral questions, defaulting to focus groups, or demanding analytics answers from a thin beta — and end up with confident wrong answers. This Skill turns one research question into one defensible method choice before any study is planned or instrument written. ## Core Features & Use Cases - Three-axis method matching: Classifies the question on attitudinal/behavioral, qualitative/quantitative, and context-of-use dimensions, then filters NN/g's 20-method landscape plus the Discover/Explore/Test/Listen stage map. - Constraint pass: Applies participant access, product maturity, traffic, budget, and team-skill constraints in order, demoting a primary to backup without ever flipping an axis. - Structured recommendation output: Produces one primary method, one backup, and named rejects — each reject tied to the specific axis or constraint it fails — plus evidence flags for unverified assumptions. - Use Case: A stakeholder asks "Do people find the booking flow easy?" The Skill sharpens it into behavioral sub-questions, rejects the proposed survey (say ≠ do), and recommends moderated remote usability testing with an unmoderated panel as backup. ## Quick Start Ask the AI to recommend the right UX research method for your research question, with a primary, a backup, and reasons the alternatives fail.
